[HTML][HTML] Forecasting: theory and practice
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
Which sentiment index is more informative to forecast stock market volatility? Evidence from China
C Liang, L Tang, Y Li, Y Wei - International Review of Financial Analysis, 2020 - Elsevier
In this paper, we investigate the predictive ability of three sentiment indices constructed by
social media, newspaper, and Internet media news to forecast the realized volatility (RV) of …
social media, newspaper, and Internet media news to forecast the realized volatility (RV) of …
How is machine learning useful for macroeconomic forecasting?
P Goulet Coulombe, M Leroux… - Journal of Applied …, 2022 - Wiley Online Library
Summary We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by
adding the how. The current forecasting literature has focused on matching specific …
adding the how. The current forecasting literature has focused on matching specific …
[HTML][HTML] Global financial stress index and long-term volatility forecast for international stock markets
C Liang, Q Luo, Y Li, LDT Huynh - Journal of International Financial …, 2023 - Elsevier
In this study, we examine the long-term predictive role of the global financial stress index
(GFSI) on equity market volatility and provide a comprehensive analysis using GFSI for the …
(GFSI) on equity market volatility and provide a comprehensive analysis using GFSI for the …
Uncertainty and crude oil market volatility: new evidence
C Liang, Y Wei, X Li, X Zhang, Y Zhang - Applied Economics, 2020 - Taylor & Francis
The main goal of this paper is to investigate the predictability of five economic uncertainty
indices for oil price volatility in a changing world. We employ the standard predictive …
indices for oil price volatility in a changing world. We employ the standard predictive …
Forecasting oil price volatility: Forecast combination versus shrinkage method
In this paper, we compare the predictive ability between forecast combination and shrinkage
method in the prediction of oil price volatility. Our investigation is based on the …
method in the prediction of oil price volatility. Our investigation is based on the …
Is implied volatility more informative for forecasting realized volatility: An international perspective
Inspired by the commonly held view that international stock market volatility is equivalent to
cross‐market information flow, we propose various ways of constructing two types of …
cross‐market information flow, we propose various ways of constructing two types of …
Which uncertainty is powerful to forecast crude oil market volatility? New evidence
X Li, Y Wei, X Chen, F Ma, C Liang… - International Journal of …, 2022 - Wiley Online Library
This paper focuses on distinguishing the predictive power of five newly developed
uncertainty indices, that is, global and US economic policy uncertainty (GEPU and US EPU) …
uncertainty indices, that is, global and US economic policy uncertainty (GEPU and US EPU) …
Global equity market volatilities forecasting: a comparison of leverage effects, jumps, and overnight information
C Liang, Y Li, F Ma, Y Wei - International Review of Financial Analysis, 2021 - Elsevier
This study extends the HAR-RV model to detailedly compare the role of leverage effects,
jumps, and overnight information in predicting the realized volatilities (RV) of 21 …
jumps, and overnight information in predicting the realized volatilities (RV) of 21 …
Forecasting crude oil futures market returns: A principal component analysis combination approach
Y Zhang, Y Wang - International Journal of Forecasting, 2023 - Elsevier
To improve the predictability of crude oil futures market returns, this paper proposes a new
combination approach based on principal component analysis (PCA). The PCA combination …
combination approach based on principal component analysis (PCA). The PCA combination …